Earthquake Early Warning Systems (EEWS), based on real-time prediction of ground motion or
structural response measures, may play a role in reducing vulnerability and/or exposition of
buildings and lifelines. In fact, recently seismologists developed efficient methods for rapid
estimation of event features by means of limited information of the P-waves. Then, when an event is
occurring, probabilistic distributions of magnitude and source-to-site distance are available and the
prediction of the ground motion at the site, conditioned to the seismic network measures, may be
performed in analogy with the Probabilistic Seismic Hazard Analysis (PSHA). Consequently the
structural performance may be obtained by the Probabilistic Seismic Demand Analysis (PSDA), and
used for real-time risk management purposes. However, such prediction is performed in very
uncertain conditions which have to be taken into proper account to limit false and missed alarms. In
the present study, real-time risk analysis for early warning purposes is discussed. The magnitude
estimation is performed via the Bayesian approach, while the earthquake localization is based on the
Voronoi cells. To test the procedure it was applied, by simulation, to the EEWS under development
in the Campanian region (southern Italy). The results lead to the conclusion that the PSHA,
conditioned to the EEWS, correctly predicts the hazard at the site and that the false/missed alarm
probabilities may be controlled by set up of an appropriate decisional rule and alarm threshold.